In an imaging system, the areas of the image sensing device receiving no incident light should be reproduced as black in the displayed image, such as a photographic print or an image on a CRT monitor. Photographic prints are often of objectionable quality if areas of the image that should be black are lighter than black. This problem is referred to as the “smoky black” problem because such images have an appearance that areas or objects that should appear dark or black appear too light. For example, consumer photographs of fireworks generally contain large regions with little or no light exposure. Fireworks images are often printed too light, resulting in images with smoky black or gray backgrounds which are not satisfactory.
For photographic negatives, the areas of the film receiving no exposure have a minimum density called Dmin. Dmin is also sometimes referred to as mask or base density. It is common to use the value of Dmin in the processing of digital images for the purpose of improving image quality. For example, in U.S. Pat. No. 5,081,485, issued Jan. 14, 1992, Terashita describes a method of using a mask density to improve the exposure estimate for an image. To this end, the mask density is subtracted from the average density. This increases the robustness of the determined color balance by decreasing the variability between different color negative films. However, Terashita's method does not ensure that regions of an image sensing device receiving little or no light exposure are mapped to substantially black in an output image.
In U.S. Pat. No. 5,781,315, issued Jul. 14, 1998, Yamaguchi describes a method of processing photographic film images which involves using the Dmin value to apply a nonlinear correction to the digitized version of the image. The Dmin values allow for increased accuracy in correction of contrast in the toe portion of the photograph. Additionally, Yamaguchi describes a method for decreasing the chroma of low chroma pixels, especially of underexposed pixels. Yamaguchi's method does not ensure that regions of a image sensing device receiving little or no light exposure are mapped substantially to black in an output image.
A method of correcting for the non-linearities in the response of photographic film is described in U.S. Pat. No. 5,134,573, issued Jul. 28, 1992 to Goodwin. This method uses the film Dmin to apply a nonlinear correction by first shifting each channel of the digital color image by an amount such that actual Dmin values match standard Dmin values and then applying the nonlinear correction to extend the linear range of the photographic film. Goodwin's method does not ensure that regions of a image sensing device receiving little or no light exposure are mapped substantially to black in an output image.
In addition, automatic exposure determination algorithms, or scene balance algorithms, estimate and apply balance adjustments which are required by both digital and optical imaging systems. These algorithms are used in high speed optical printers or in Photo-CD scanners. For example, U.S. Pat. No. 4,668,082, issued May 26, 1987 to Terashita et al.; U.S. Pat. No. 4,945,406 issued Jul. 31, 1990 to Cok; and U.S. Pat. No. 5,978,100 issued Nov. 2, 1999 to Kinjo, all describe automatic exposure determination algorithms. Generally, these algorithms are based on regressions between aim balances and image features. None of these methods describe a method of ensuring that regions of a image sensing device receiving little or no light exposure are mapped substantially to black in an output image.
Finally, contrast modification methods exits to modify the contrast of images. For example U.S. Pat. No. 6,204,940 issued Mar. 20, 2001 to Lin et al. describes a method image contrast modification employing a step of white/black point mapping. Black point mapping techniques typically involve determining the code value corresponding to a specific (low) percentage point of the cumulative histogram and mapping that code value to a desired code value, usually with a look-up-table (LUT). While such methods can guarantee that the resulting output image will contain black or dark pixels or regions, this technique can damage images of scenes not having any black regions. For example, a photograph of the ocean may be a relatively low contrast image showing the beach and sky with no dark areas. However, applying black point mapping would necessitate that the darkest regions of the image be mapped to black (or very dark) in the output image. This technique often damages image quality by forcing the image to contain black, thereby severely increasing the contrast of the image. Without prior knowledge of the capture system or semantic knowledge of the scene, it is very difficult to determine whether areas of an image actually appeared “black” in the original scene.
Therefore, there exists a need for an improved method and system of image processing that ensures that regions of an input image corresponding to little or no light received by an image capture medium are reproduced as dark regions in an output image without severely increasing image contrast.